Agricultural Meteorology
N. Torabinezhad; A. Zarrin; A.A. Dadashi-Roudbari
Abstract
Introduction
Drought is a costly natural hazard with wide-ranging consequences for agriculture, ecosystems, and water resources. The purpose of this research is to determine the characteristics of drought and its types in Iran during the last four decades. Drought turns into different types in the water ...
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Introduction
Drought is a costly natural hazard with wide-ranging consequences for agriculture, ecosystems, and water resources. The purpose of this research is to determine the characteristics of drought and its types in Iran during the last four decades. Drought turns into different types in the water cycle and imposes many negative consequences on natural ecosystems and different socio-economic sectors. According to International Disaster Database (EM-DAT), drought accounts for 59% of the economic losses caused by climate change. Many parts of the world have experienced extensive and severe droughts in recent decades. In Iran, droughts have occurred frequently during the last four decades and have become more severe in the last decade.
Materials and Methods
In this research, we used precipitation, temperature, wind speed, and sunshine hours of 49 synoptic meteorological stations during 1981-2020. Drought has been investigated with The Standardized Precipitation-Evapotranspiration Index (SPEI) in four scales of 3, 6, 12, and 24 months, which represent meteorological, agricultural, hydrological, and socio-economic droughts. To calculate the SPEI, the precipitation variable (P) is analyzed with the cumulative difference between P and potential evapotranspiration (PET). In other words, surplus/deficit climate water balance (CWB) is considered. The FAO Penman-Monteith method was used to calculate PET. Then, using the RUN theory, the characteristics of drought, including its magnitude, duration, intensity, and frequency, were determined for all four investigated scales.
Results and Discussion
The results showed that the frequency of drought events fluctuates from a minimum of 12.13% to a maximum of 18.13% in different regions of the country during 1981-2020. The climatological study of drought characteristics shows that the most frequent drought events occurred in the west, southwest, and southern coasts of the Persian Gulf and northwest of Iran compare to other regions of the country. This is while the duration of the drought period is longer in the eastern and interior regions of Iran. Examining the types of droughts shows that more than 60% of the droughts occurring in Iran are moderate droughts. Moderate and severe droughts are mostly seen in the west, southwest, and northwest of Iran. The duration of Iran's drought varies from at least 3 months in meteorological drought to more than 8 months in socio-economic drought. Therefore, droughts are more frequent in the western regions and longer in the eastern regions. The intensity of drought is also higher in the eastern and interior regions than in the western and northwestern regions of Iran. The decadal changes of drought show that the duration and magnitude of drought in Iran have increased and the severity of the drought has decreased during recent decades.
Conclusion
The intensity, magnitude, and duration of the drought period in Iran increased with the increase of the investigated scales from 3 months to 24 months. Examining the average frequency of drought showed that as we move from meteorological drought to socio-economic drought, the frequency of drought increases, which confirms the previous findings. The eastern and southeastern parts of Iran have experienced a longer duration and larger magnitude of drought than the western and northwestern Iran, which can be caused by the climate conditions of this region, i.e., high temperature and evapotranspiration and less precipitation, and seasonality.
The maximum magnitude of drought in Iran is related to socio-economic drought (SPEI-24) followed by hydrological drought (SPEI-12). This characteristic has increased especially in the last two decades (2001-2020) compared to the previous decades (1981-2000). This is while the magnitude of meteorological (SPEI-3) and agricultural (SPEI-12) droughts do not increase much in the last two decades compared to the previous decades.
Anthropogenic activities play a more prominent role in increasing the magnitude of socio-economic (SPEI-24) and hydrological (SPEI-12) droughts than natural forcing. With the construction of many dams and the digging of countless deep wells, as well as changing the direction of rivers, the water cycle has been completely affected by human activities during the last four decades in Iran. Obviously, anthropogenic activities play an important role in increasing the magnitude of hydrological and socio-economic droughts. In contrast, meteorological and agricultural droughts have not shown many changes in Iran.
The results of the decadal average of drought intensity showed that this characteristic of drought in the last decade (2011-2020) has decreased compared to previous decades (1981-2010). On the other hand, as mentioned earlier, the magnitude and duration of drought, especially for hydrological and socio-economic droughts, have increased in the last two decades (2001-2020). Therefore, the reason for the decrease in the severity of the drought has a statistical explanation before it has a climatic reason because the severity of the drought is calculated by dividing the magnitude of the drought by its duration.
Mahsa Sameti; Seied Hosein Sanaei-Nejad; Firoozeh Rivaz; Bijan Ghahraman
Abstract
Introduction: Drought is a very complex natural phenomenon which changes with time and space. Spatial and temporal variations of drought are analyzed separately. Geostatistical methods can be used for spatiotemporal analyses to find related spatial and temporal pattern changes. These methods, ...
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Introduction: Drought is a very complex natural phenomenon which changes with time and space. Spatial and temporal variations of drought are analyzed separately. Geostatistical methods can be used for spatiotemporal analyses to find related spatial and temporal pattern changes. These methods, which use the spatio-temporal data, considering the spatial position of the data relative to each other, also take into account their temporal dependence. If needed, they can estimate values of their variable at any location and any time. Moreover, the drought spatial variations in the studied region can be drawn at every desired period. On the other hand, it is expected that intervening of the time dimension in the equations of these methods, as compared to the purely spatial methods, provide more precision in estimating the values of drought indices, which is studied in this research.
Materials and Methods: Monthly rainfall data of 48 stations in the northeast of Iran for the period of 1981-2012 were used in this study. The SPI drought index is calculated for the 12-month time scale. Data were divided into two groups of training data from 1981-2011 and experimental data of 2012. After analyzing the data regarding their stationarity and isotropic assumptions, the spatiotemporal data were formed and their spatiotemporal empirical variogram was drawn. Furthermore, the purely spatial and temporal variograms for the zero space and time steps were also drawn. Then, four models of the spatiotemporal variogram functions were applied on the training data. The performance of these models was tested and compared by estimating the parameters of the model based on the Square Error (MSE). Moreover, three-dimensional fitted variograms were drawn for different models. Mean The best spatiotemporal variogram model was selected by comparing the models prediction with experimental data using the Mean Square Prediction Error (MSPE). Using spatiotemporal kriging method, the predicted values of experimental data were interpolated and that of the observed values were interpolated by kriging method. Cross validation on experimental data was also performed using RMSE, MAE, ME and COR. Then spatiotemporal and purely spatial variogram models were investigated and compared.
Results and Discussion: The results showed that the 12-month SPI index had no spatial trend but had a decreasing trend against the time. Hence, a simple regression equation was used for fitting the trend of the data. After detrending the data, the SPI index values were considered as the dependent variable, while the time was taken as the independent variable. On the other hand, drawing the variogram in different directions (0°, 45°, 90°, and 135°) had no significant effect relative to each other, and the hypothesis of isotropic state was accepted. The plots of purely spatial and temporal variograms showed that the spherical variogram for space and the linear variogram for the time would have the best fitting. The empirical 3-D and 2-D spatiotemporal variograms of the training data were plotted. The empirical 3-D variogram showed that the data had reached to its temporal sill in a 1-year time lag, and had reached to its spatial sill, in about 25-kilometers, which are in conformity with the purely spatial and temporal variograms. The comparison of different variogram functions showed that the MSE values of the separable, metric, product-sum and sum-metric models were 0.00139, 0.00295, 0.00111, and 0.00112, respectively, the last two of which had fewer errors. Drawing the spatiotemporal variogram of these functions showed that the spatiotemporal variogram of product-sum and sum-metric models have more similarity to the sample one. Regarding the selection of the best model, the MSPE statistics of the product-sum and sum-metric models were 0.281 and 0.389, respectively. Therefore, the product-sum model could be selected as the best model. The least rate of errors was found in the exponential variogram model for space, and in the linear variogram for the time. The parameters of the nugget effect, partial sill and range for the spatial variogram would be 0.00, 0.063, and 5.78, and for the temporal variogram would be 0.00, 0.635, and 1.044, respectively. After predicting values of 12-month SPI in 2012 by the product-sum variogram model and adding the values of the trend, they were interpolated by using the spatiotemporal kriging, and the observed values were interpolated by the use of kriging. The obtained plot from the predicted values had great similarity with that of the observed values, which indicates the appropriate capability of the model in predicting the unobserved values. The cross-validation of different spatiotemporal and the spatial models with 25 and 47 neighborhoods showed that the performance of the models had no significant differences relative to each other, and they also had no better performance relative to the purely spatial model.
Conclusion: The results of this study showed that the product-sum model had a better performance among different spatiotemporal variogram models in predicting the 12-month SPI values of 2012. However, the performances of different spatiotemporal models were quite close to each other. There is no significant difference that could be observed between spatiotemporal and purely spatial models. Also, it is proposed to use the dynamic spatiotemporal models and the results to be compared with the classical models.
Mohammad Ghabaei S; Hamid Zare Abyaneh; Abolfazl Mosaedi; S. Zahra Samadi
Abstract
Introduction: Drought is a recurrent feature of climate that caused by deficiency of precipitation over time. Due to the rise in water demand and alarming climate change, recent year’s observer much focus on drought and drought conditions. A multiple types of deficits and relevant temporal scales can ...
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Introduction: Drought is a recurrent feature of climate that caused by deficiency of precipitation over time. Due to the rise in water demand and alarming climate change, recent year’s observer much focus on drought and drought conditions. A multiple types of deficits and relevant temporal scales can be achieved through the construction of a joint indicator that draws on information from multiple sources and will therefore enable better assessment of drought characteristics including return period, persistent and severity. The Standardized Precipitation Evapotranspiration Index (SPEI) combines information from precipitation and temperature in the form of water surplus or deficit according to Standardized Precipitation Index (SPI). Rainfall over some regions of Iran during some resent year was below average while mean and maximum temperatures were very high during this period, as was evaporation. This would suggest that drought conditions were worse than in previous recent periods with similarly low rainfall. The main objective of this study is to assess the influences of humidity on the SPEI index and investigate its relation with SPI and Reconnaissance Drought Index (RDI) over six different climatic regions in Iran.
Materials and Methods: Iran has different climatic conditions which vary from desert in central part to costal wet near the Caspian Sea. In this study the selection of stations was done based on Alijani et al (2008) climatic classification. We chose 11 synoptic stations from six different climatic classes including costal wet (Rasht and Babolsar), semi mountains (Mashhad and Tabriz), mountains (Shiraz and Khoram Abad), semi-arid (Tehran and Semnan), arid (Kerman and Yazd) and costal desert (Bandar Abas). The Meteorological datasets for the aforementioned stations were obtained from the Iran Meteorological Organization (IRIMO) for the period 1960-2010. The compiled data included average monthly values of precipitation, minimum and maximum air temperature, mean relative humidity, sunshine hours) and wind speed at 2 m height. A probability-based overall water deficit assessment was achieved from multiple drought-related indices (i.e. SPEI, SPI and RDI). The humidity conditions were monitored for given stations based on each index during annual, short term (1, 3 and 6 months) and long term (9 , 12, 18 and 24 months) periods. This research further examine the Locally Weighted Scatter plot Smoothing (LOWESS) graphical method and nonparametric Man- Kendal test to evaluate the trends associated with humidity deficiency in annual and monthly time scales during 51 years period (i.e. 1960-2010).
Results and Discussion: Our results revealed that the maximum correlation between SPEI index with indices of SPI and RDI was achieved in the coastal wet region and with a declining trend in relative humidity condition in the rest of the regions, this correlation is down over both short- and long-term periods. A comparison between SPI and SPEI also performed that the SPI index was able to reflect prolonged drought over the costal wet region where it showed significant inconstancy in desert and semi desert regions. SPEI result suggested substantial deficiencies in relative humidity at the beginning of 1997 during long term period which indicated an increasing trend of drought statues during last decades. Overall, according to the results of SPEI index in 1month periods monthly drought assessment showed a declining trend in drought magnitude during autumn, winter and spring season months (October to June) at investigated stations excepts Tehran and Shiraz stations and with a potential deficiency in relative humidity conditions. Unlikely, annual trend showed increasing trends in drought frequency and persistent over last decade.
Conclusion: Our results can be summarized as below:
Focusing on various types of deficits, the result of humidity based deficiencies indicated that for semi-mountains, mountains, semi-arid, arid and costal desert regions the period of 1997 to 2010 has a large total moisture shortage over all climatic regions. Most of the climate stations showed moisture deficits (decline trends) during October to June (9-month) at many stations expect Tehran and Shiraz stations which revealed a significant increasing over 51 years. We recommend using SPEI index for arid and semi-arid regions because it includes temperature variability in drought model so it reflects drought conditions better than other indices. Furthermore, three drought indices (i.e. SPEI, SPI and RDI) have similar sensitivity to water deficits over wet climatic regions; therefore, each of those indices can be used.
M. Rahmati; Gh. Davarynejad; Mohammad Bannayan Aval; M. Azizi
Abstract
In order to study the sensitivity of vegetative growth to water deficit stress of a late-maturing peach (Prunus persica L. cv. Elberta) under orchard conditions, an experiment was conducted as randomized complete-block design with three treatments and four repetitions in Shahdiran commercial orchard ...
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In order to study the sensitivity of vegetative growth to water deficit stress of a late-maturing peach (Prunus persica L. cv. Elberta) under orchard conditions, an experiment was conducted as randomized complete-block design with three treatments and four repetitions in Shahdiran commercial orchard in Mashhad during 2011. Three irrigation treatments including 360 (low stress), 180 (moderate stress) and 90 (severe stress) m3ha-1week-1 using a drip irrigation system (minimum stem water potential near harvest: -1.2, -1.5 and -1.7 MPa, respectively) from the mid-pit hardening stage (12th of June) until harvest (23rd of Sep.) applied. Predawn, stem and leaf water potentials, leaf photosynthesis, transpiration, stomatal conductance and leaf temperature, the number of new shoots on fruit bearing shoots and vegetative shoots lengths during growing season as well as leaf area at harvest were measured. The results showed that water deficit stress had negative effects on peach tree water status, thereby resulting in decreased leaf gas exchange and tree vegetative growth. As significant decreased assimilate production of tree was resulted from both decreased leaf assimilation rate (until about 23 % and 50 %, respectively under moderate and severe stress conditions compared to low stress conditions) and decreased leaf area of tree (until about 57% and 79%, respectively under moderate and severe stress conditions compared to low stress conditions at harvest). The significant positive correlation between leaf water potential and vegetative growth of peach revealed that shoot growth would decrease by 30% and 50% of maximum at leaf water potential of –1.56 and –2.30 MPa, respectively.
A. Pourhaghi; F. Radmanesh; A. Maleki
Abstract
Introduction : Sustainable development of groundwater resourcesrequires a proper assessment of available resources, understanding of system behavior and interaction between groundwater and surface water.In recent years, a Delfan plain (in Iran) is facing a sharp decline in groundwater levels due to increasing ...
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Introduction : Sustainable development of groundwater resourcesrequires a proper assessment of available resources, understanding of system behavior and interaction between groundwater and surface water.In recent years, a Delfan plain (in Iran) is facing a sharp decline in groundwater levels due to increasing in population and exploitation of groundwater resources.In this study, using modflow model effect of drought and wet conditions on water table fluctuations of Delfan plain aquifer was evaluated.
Materials and Methods: Delfan plain is one of the Lorestan Plains (in Iran Country) and located in the north of the Lorestan Province, around the city ofNurabad (Delfan).Precipitation survey of the region shows that the average annual rainfall in the plains is 480 mm and aquifers of the region has 10 piezometric wells. Drawing of the groundwater hydrograph from 2004 to 2013 shows that the general trend of the groundwater level is downward, which represent decreasing in groundwater resources of the region. At the beginning of the modeling process using Modflow model, after gathering all the required information, conceptual model of the plain was generated. To preparing this model, various data such as topographic maps, geophysical data, logs of wells, pumping tests and observation wells data and flow data taken from exploitation wells was used. Water level data of October 2007 which has the lowest fluctuation was used for the calibration of steady state.In this step with model successive run, hydraulic conductivity is optimized. After model calibration in the steady state, do same in the unsteady state.Specific discharge was optimized at this step.After calibration in the unsteady state, model needs verification to be trusted.For this purpose, verification was done in November 2012 to November 2014.After calibration and validation of the model, the model was carried out under drought and wet conditions.Drought is one of the environmental disasters that its occurrence could bring the water challenges in the field of quality and quantity. Because of drought and lack of rainfall affect groundwater resources, soil moisture and river flow, used index called Standard Precipitation Index (SPI) to quantify the impact of rainfall in of 3, 6, 12, 24-month period.This index is calculated based on long-term statistics.
Results Discussion :In steady state, the model's sensitivity is studied according to changes in hydraulic conductivity value and discharge of pumping wells and in the unsteady state according to specific yield and other parameters was investigated. Based on this analysis in steady state, generally it can be said that the model is more sensitive to the exploitation wells. In unsteady state, the model is more sensitive to specific yield and hydraulic conductivity and other parameters are in the next level.With SPI reviewing of 120-months, it was seen that the plain in 1984 and 1993 has the lowest 120-month SPI with the value of -1.08 (with average precipitation value of 423 mm).For applying virtual wet period with 30-years precipitation reviewing, it was observed that years of 2001 and 2010 have the most 120-month SPI value with value of 1.86 (with average precipitation value of 587 mm).For applying the virtual wet conditions in the next step, the model was simulated with the rainfall data of 2001 and 2010.To decrease the water table drop, considering the amount of drop and water needs of the region, several runs were performed which ultimately results showed to offset the drop in these three exploitation areas, the discharge of exploitation wells must be reduce 20% that This strategy is able to reduce the average annual rate of water table drop for the next 10 years. Finally, after model’s run and piezometers drop, plain model was used to obtain groundwater balance.
Conclusion: The model implementation in drought and wet conditions shows that in these conditions the groundwater level decreases with the average of (-7.80m) and (-5.83m), respectively. which with the 20 % decrease of the discharge of the exploitation wells in these conditions, the level groundwater and aquifer balance improves.For the next ten years in the normal condition or present situation of exploitation, plain balance is -83.20 million cubic meters which by 20% reduction in wells exploitation, this water balance is predicted -41.20 million cubic meters for next 10 years.In the drought conditions Delfan aquifer water balance is predicted as -91.20 million cubic meters during ten years which by 20% reduction of wells exploitation this water balance increases to -49.20 million cubic meters.
behrouz hosseini; yaghoub dinpazhoh; J. Nikbakht
Abstract
Introduction: Drought is a creeping natural phenomenon, which can occur in any region. Such phenomenon not only affects the region subjected to drought, but its adverse effects can also be extended to other adjacent regions. This phenomenon mainly starts with water deficiency (say less than long- term ...
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Introduction: Drought is a creeping natural phenomenon, which can occur in any region. Such phenomenon not only affects the region subjected to drought, but its adverse effects can also be extended to other adjacent regions. This phenomenon mainly starts with water deficiency (say less than long- term mean of variable under study such as rainfall, streamflow, groundwater level or soil moisture) and progress in time. This period can be ended by increasing the rainfall and reaching the mean level. Even after the ending of a drought period, its adverse effects can be continued for several months. Although, it is not possible (at least at this time) to prevent the occurrence of drought in a given region, it is not impossible to alleviate the drought consequences by scientific water management. Such a management should be employed before drought initiation as well as during it and continue on even after the end of the drought period. The frequency of the main drought characteristics is a major concern of this study. The Northwest of Iran recently encountered severe and prolonged droughts, such that a major portion of the Urmia Lake surface disappeared during the last drought in recent years. In order to study drought characteristics, we used the Reconnaissance Drought Index (RDI). This index is based on annual rainfall and potential reference crop evapotranspiration (abbreviated by PET here). This study employed the Monte Carlo simulation technique for synthetic data generation for analysis.
Materials and Methods: The information from the 17 synoptic weather stations located in the North-west of Iran was used for drought analysis. Data was gathered from the Islamic Republic of Iran’s Meteorological Organization (IRIMO). In the first stage of research, the ratio of long term mean annual precipitation to evapotranspiration was calculated for each of the stations. For this purpose, the Penman-Montheis (FAO 56) method was selected for PET estimation. In the second stage, the 64 candidate statistical distributions were fitted for the mentioned RDI’s of each station. The best statistical distribution was selected among the 64 candidate distributions. The best fitted distribution was identified by the chi-square criterion. The parameters of the distribution were estimated by the Maximum Likelihood Estimation (MLE) scheme. Then 500 synthetic time series (each of them have the same number of observed data) were generated employing the parent population parameters. The three main drought characteristics (namely duration, severity and magnitude) were obtained for each of the mentioned artificial time series. The maximum values for each of the mentioned drought characteristic were selected for each year. Then, a new time series having the 500 elements were obtained by collecting the chosen values for each station. Once again the best distribution was selected for each series. Drought characteristics for different return periods (2, 10, 25, 50, 100 and 200 years) were estimated for each station.
Results and Discussion: Preliminary results indicated that a negative trend existed in annual rainfall time series for almost all of the stations. On the other hand, the pattern of monthly PET histograms were more or less similar for all of the selected stations. The peak of the PET was mainly observed in the hottest month of year, whereas the lowest value of the monthly PET belonged to the coldest month of year. The results showed that the amount of annual rainfall time series decreases sharply, after the year 1991. However, PET values significantly increase for all of the selected stations. After calculation of RDI values, the histogram of annual RDI’s was plotted against the year. This is repeated for all of the selected stations. Figure. 6 shows the mentioned diagram for Tabriz station as an example. In the mentioned Figure, negative values of RDI (shown by red bars) indicated the drought years. A critical prolonged drought with a sixteen years duration period (neglecting the 2001 in which RDI value was a small positive value) was experienced in Tabriz. The maximum drought severity in Tabriz was estimated to be about -7 in RDI units. Urmia station experienced the longest drought period, starting from 1995 and ending in 2005. It can be concluded that although few sparse wet years were observed in some of the selected stations in the studied period, they cannot compensate the water deficiency accumulated during several consecutive years. The results showed that the lowest value of the ratio of drought severity in a 100 year return period to the corresponding value for 2 year return period was about 2.13 (belonged to the Tabriz station), whereas the highest value was 3.17 (belonged to the Tekab station). On the other hand, the lowest value for the ratio of drought duration in 100 year return period to its corresponding value for 2 year return period was 1.95 (experienced in the Makoo station). The highest mentioned ratio was 9.18 (observed in the Sardasht station). The lowest and highest value of the ratio of drought magnitude in 100 year return period to its corresponding value for 2 year return period were 1.17 and 2.74, respectively. The mentioned drought magnitude ratios were observed in the Urmia and the Khalkhal stations, respectively. The isoplethes of the three main drought characteristics (severity, magnitude, duration) for a 10 year return period was illustrated for the study area (Northwest of Iran).
Conclusion: In the present study RDI values were used to analyze drought characteristics of Northwest of Iran. The Penman-Montheis method was used to estimate PET (needed for RDI) values of the stations. The main three drought characteristics were calculated for each of the 500 synthetic time series. The results showed that nearly all of the areas under study experienced severe and prolonged droughts. It can be concluded that a sharp decrease in annual precipitation as well as the increase in PET (due to greenhouse effects of consuming fossil fuels as the main source of energy in the region) from 1995 to 2005 was observed in the study area. Scientific management of available water in the study area is extremely vital to alleviate the adverse consequences of drought. Several economic and social problems were anticipated in these arid and semi-arid regions of Iran.
H. Zareabyaneh; M. GHobaeisoogh; Abolfazl Mosaedi
Abstract
Introduction: Drought is a natural and recurrent feature of climate. The characterizations of it may change under the effect of climate change in future periods. During the last few decades a number of different indices have been developed to quantify drought probabilities. Droughts are caused by disruptions ...
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Introduction: Drought is a natural and recurrent feature of climate. The characterizations of it may change under the effect of climate change in future periods. During the last few decades a number of different indices have been developed to quantify drought probabilities. Droughts are caused by disruptions to an expected precipitation pattern and can be intensified by unusually high temperature values. Precipitation-based drought indices, including the Standardized precipitation index (SPI), cannot identify the role of temperature increase in drought condition and in addressing the consequences of climate change. Recently, two new standardized drought indices have been proposed for drought variability analysis on multiple time scales, the Reconnaissance Drought Index (RDI, Tsakiris et al., 2007) and the Standardized Precipitation Evapotranspiration Index (SPEI, Vicente-Serrano et al., 2010). The objective of this study is to evaluate the characterization of wet and dry periods under the effect of climate change according to SPEI index in synoptic station of Hamedan for the next thirty years (2011-2040).
Materials and Methods: In this study, the indices of SPEI, SPI and RDI were investigated and the SPEI index as a multiscalar and suitable index was used to detect, monitor, and explore the consequences of global warming on drought conditions in synoptic station of Hamedan (airport). For this purpose, the period of 1981-2010 was chosen as the base period and the simulation of the future climate variables were done based on A1B, A2 and B2 emissions scenarios and performance of multi model ensemble via LARS-WG5 model for the period of 2011-2040. The performance of the multi model ensemble was done by using five global climate models including IPCM4, MPEH5, HADCM3, GFCM21, and NCCCS in the IPCC Fourth Assessment Report (Semenov and Stratonovitch, 2010). By simulating the values of precipitation ,and the values of temperature and the values of estimated evapotranspiration , the values of SPEI, RDI and SPI indices were calculated annually and 1, 3 and 6 months (short- term period) and 12, 18 and 24 months (long- term period) time scales for the base period and the three next decades. Then, the relation among them was computed and investigated via correlation coefficient. Then, by monitoring the humidity condition via SPEI index, the characterization of wet and dry periods including period numbers, longest period, total deficit or surplus, and maximum deficit or surplus were derived based on Run theory and were comprised for the base period and three future decades.
Results and Discussion: Evaluation of LARS-WG5 model for base period showed that the model was able to simulate minimum and maximum temperatures and precipitation data with high accuracy based on statistic error and can be used to generate data for future years according to emission scenario. According to the simulated results of performance of multi model ensemble, the average values of mean temperature and precipitation will increase by 0.820C and 2.5 % for A2 scenario, respectively. In addition, the minimum and maximum temperatures have increased in all of the months according to the three scenarios in comparison with the base period. The correlation results between the investigated indices showed that the maximum and minimum of correlation can be observed between SPI & RDI and SPEI & SPI indices in the base period and future decade for each scenario, respectively. Drought assessment based on the SPEI index in the base period shows that the main drought episodes occurred in the 1999 to 2001 that were consistent with FAO report (2006). Comparison of wet and dry periods in relation to the base period showed that the number of dry periods will increase in time scales of 1 and 3 months and will decrease in other long-term time scales.
Conclusion: Climate change and its effects are among the main challenges of water resources management in the present century. In this study, the effects of this phenomenon on drought monitoring and change of characterizations were investigated. For this purposes, we used daily meteorological variables during thirty years (1981-2010) from Hamedan Synoptic station. The results of drought monitoring were based on SPEI index, and it revealed the high variability of humidity condition in the first decade of simulation in comparison with the second and third decades. This issue indicated that this decade requires more attention and management measurements. Also, according to the results of the derived characterization via Run theory, the number of dry periods will decrease and persistence of the longest dry period and consequently the volume of deficit will increase in the next three decades. In addition, the total volume surplus of wet periods will decrease in relation to the base period that can be interpreted as the increasing of moisture deficit in future decades The SPEI is based on precipitation and temperature data, and it has the advantage of combining multiscalar character with the capacity to include the effects of temperature variability on drought assessment. Thus, we recommend SPEI, as a suitable index for studying and identifying the effect of climate change on drought conditions.
Gh. Kavakebi; M. Mousavi Baygi; A. Mosaedi; Mehdi Jabbari Nooghabi
Abstract
Drought is a natural creeping event that starts due to lower moisture compared to normal condition. This phenomenon impacts all aspects of human activities. However there is neither any detailed definition nor a general and proper index for drought monitoring In the present study using the Drought indices ...
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Drought is a natural creeping event that starts due to lower moisture compared to normal condition. This phenomenon impacts all aspects of human activities. However there is neither any detailed definition nor a general and proper index for drought monitoring In the present study using the Drought indices SPI and RDI to monitor drought in 10 synoptic stations in the province were studied over a period of 24 years(1991-2010). After using panel data analysis of annual and seasonal drought tried to detecte effective the parameters above were measured using two indicators. Based on the results of monitoring Drought was found a severe drought that the 2008 in the province. Also, analyse of Panel data was show all six parameters mean of maximume tempretuer, mean of minimum tempreture, sun shine, precipitation, relative humidity and mean wind speed in 2 meters that to calculate the drought index RDI, not required to calculate Drought in time scale of annual and seasonal in 10 stations; due time scale, only of some these parameters are required. Based on SPI, precipitation is necessary for time scale annual and seasonal droghut.
sajjad ebrahimzadeh; javad bazrafshan
Abstract
Drought can affects by reduced water resources, agricultural productivity, change in vegetation cover, and accelerate the desertification of areas. In order to drought monitoring, we need to quantify drought effects by using drought indices. These indices based on type of available data are divided ...
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Drought can affects by reduced water resources, agricultural productivity, change in vegetation cover, and accelerate the desertification of areas. In order to drought monitoring, we need to quantify drought effects by using drought indices. These indices based on type of available data are divided into two general categories of ground- and satellite- based indices. The aim of this study was to compare the capability of detection and classification of vegetation changes occurred due to the drought, between one ground-based drought index (Standardized Precipitation Index (SPI)) and four satellite drought indices derived from AVHRR-NOAA (normalized difference vegetation index (NDVI), temperature condition index (TCI), ratio vegetation index (RVI), standardized vegetation index (SVI) in the Kermanshah province. To do this, the change vector (CV) analysis was used as one of the important change detection algorithms. In this method, the change occurred in vegetation has been shown by two components, change magnitude and change direction. The results of implementation of the CVA on the maps of drought indices during the growing season (March to August) in selected years (two normal years, one wet year, and one drought year) showed the best response to the drought in the study years (except the wet year 1992), obtained by SVI. The lowest similarity was obtained between the SPI and TCI, for wet and normal years. Finally, the study suggests mostly the satellite indices based on the vegetation conditions, rather than the temperature indices, for assessing the effect of drought on vegetation cover.
S. Noori; S.H. Sanaei Nejad
Abstract
Because most of the methods that have been proposed for estimating statues drought generate point estimate, so researchers were always looking for ways to achieve regional estimates for better manage this gradually creeping phenomenon. Recently, remote sensing and techniques proposed base on it could ...
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Because most of the methods that have been proposed for estimating statues drought generate point estimate, so researchers were always looking for ways to achieve regional estimates for better manage this gradually creeping phenomenon. Recently, remote sensing and techniques proposed base on it could estimate drought in regional scale well. In this paper, it’s tried to estimate drought and evaluation performance of the Temperature Vegetation Dryness Index (TVDI) and the Modified Temperature Vegetation Dryness Index (MTVDI) using the vegetation and temperature MODIS products in Northern Khorasan during two years 2004 and 2008 (as normal and dry years respectively). The results showed that MTVDI index has performed better than TVDI index. The result of linear correlation analyzed between indices and the cumulative precipitation of the currently 16 days, early 16 days and early 1 month, 2 month, 3 month, 5 month and 7 month showed the indices, specially MTVDI, had a close relationship with early 1 month precipitation than the others. This is due to the delayed response of vegetation to precipitation.
M. Ghorbani Aghdam; yaghoub dinpazhoh; A. Fakheri Fard; S. Darbandi
Abstract
Having a correct view of the effective factors on climatic changes by explanation of a considerable part of the total variance in data with limited number of principal components the analytical methods of decreasing data dimensions, such as PCA are important tools in water resources planning. In this ...
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Having a correct view of the effective factors on climatic changes by explanation of a considerable part of the total variance in data with limited number of principal components the analytical methods of decreasing data dimensions, such as PCA are important tools in water resources planning. In this study factor analysis method as a tool for projecting the information space on the limited and specific axes, has been applied. The main aim of this study is regionalization of Urmia Lake basin from the view of drought using factor analysis. For this purpose monthly precipitation data of 30 weather stations in the period 1972-2009 were used. For each of the selected stations three and twelve months SPI value were calculated. Factor analysis conducted on SPI values to delineate the study area with respect to drought characteristics. Homogeneity of obtained regions tested using the S-statistics proposed by Wiltshire. Resultes of factor analysis of 3 (12) months SPI values showed that 5 (6) factors having eigen values greater than 1 acounted for 68.08 (78.88) percent of total variance. Urmia Lake basin delineated to 5 (6) distinct regions considering the eigenvectors following rotation using the 3 (12) month time scale. Results of homogeneity test indicated that all of the obtained regions were homogeneous.
